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Reliable interpretability of biology-inspired deep neural networks

Deep neural networks display impressive performance but suffer from limited interpretability. Biology-inspired deep learning, where the architecture of the computational graph is based on biological knowledge, enables unique interpretability where real-world concepts are encoded in hidden nodes, whi...

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Detalles Bibliográficos
Autores principales: Esser-Skala, Wolfgang, Fortelny, Nikolaus
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10564878/
https://www.ncbi.nlm.nih.gov/pubmed/37816807
http://dx.doi.org/10.1038/s41540-023-00310-8

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